diff options
Diffstat (limited to 'test/test_directionality.py')
| -rw-r--r-- | test/test_directionality.py | 14 |
1 files changed, 12 insertions, 2 deletions
diff --git a/test/test_directionality.py b/test/test_directionality.py index 63865cc..5c7e917 100644 --- a/test/test_directionality.py +++ b/test/test_directionality.py @@ -14,7 +14,6 @@ from numpy.testing import assert_equal, assert_almost_equal, \ import pyspike as spk from pyspike import SpikeTrain, DiscreteFunc -# from pyspike.spike_directionality import _spike_directionality_profile def test_spike_directionality(): @@ -39,7 +38,7 @@ def test_spike_directionality(): D_expected = np.array([[0, 2.0, 0.0], [-2.0, 0.0, -1.0], [0.0, 1.0, 0.0]]) assert_array_equal(D, D_expected) - dir_profs = spk.spike_directionality_profiles([st1, st2, st3]) + dir_profs = spk.spike_directionality_values([st1, st2, st3]) assert_array_equal(dir_profs[0], [1.0, 0.0, 0.0]) assert_array_equal(dir_profs[1], [-0.5, -1.0, 0.0]) @@ -87,3 +86,14 @@ def test_spike_train_order(): assert_array_equal(f.x, expected_x) assert_array_equal(f.y, expected_y) assert_array_equal(f.mp, expected_mp) + + # Averaging the profile should be the same as computing the synfire indicator directly. + assert_almost_equal(f.avrg(), spk.spike_train_order([st1, st2, st3])) + + # We can also compute the synfire indicator from the Directionality Matrix: + D_matrix = spk.spike_directionality_matrix([st1, st2, st3], normalize=False) + print D_matrix + num_spikes = np.sum(len(st) for st in [st1, st2, st3]) + print f.avrg(), num_spikes + syn_fire = np.sum(np.triu(D_matrix)) / num_spikes + assert_almost_equal(f.avrg(), syn_fire) |